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Termes IGN > imagerie > image radar > image radar moirée
image radar moiréeSynonyme(s)Interferogramme ;image SAR ;Image rso ;Image radar interférométrique Image par radar à antenne synthétiqueVoir aussi
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Multiangle BSAR imaging based on BeiDou-2 navigation satellite system: experiments and preliminary results / Tao Zeng in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)
[article]
Titre : Multiangle BSAR imaging based on BeiDou-2 navigation satellite system: experiments and preliminary results Type de document : Article/Communication Auteurs : Tao Zeng, Auteur ; Dongyang Ao, Auteur ; Cheng Hu, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 5760 - 5773 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] acquisition d'images
[Termes IGN] fusion d'images
[Termes IGN] image radar moirée
[Termes IGN] positionnement par BeiDou
[Termes IGN] positionnement par GNSS
[Termes IGN] radar bistatique
[Termes IGN] zone d'intérêtRésumé : (Auteur) This paper analyzes the multiangle imaging results for bistatic synthetic aperture radar (BSAR) based on global navigation satellite systems (GNSS-BSAR). Due to the shortcoming of GNSS-BSAR images, a multiangle observation and data processing strategy based on BeiDou-2 navigation satellites was put forward to improve the quality of images and the value of system application. Twenty-six BSAR experiments were conducted and analyzed in different configurations. Furthermore, a region-based fusion algorithm using region-of-interest (ROI) segmentation was proposed to generate a high-quality fusion image. Based on the fusion image, typical targets such as water area, vegetation area, and artificial targets were compared and interpreted among single/multiple-angle images. The results reveal that the multiangle imaging method was a good technique to enhance image information, which might extend the applications of GNSS-BSAR. Numéro de notice : A2015-754 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2430312 Date de publication en ligne : 26/05/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2430312 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78744
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 10 (October 2015) . - pp 5760 - 5773[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015101 SL Revue Centre de documentation Revues en salle Disponible Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data / Yue Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
[article]
Titre : Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data Type de document : Article/Communication Auteurs : Yue Zhang, Auteur ; Xuan Sun, Auteur ; Antje Thiele, Auteur ; Stefan Hinz, Auteur Année de publication : 2015 Article en page(s) : pp 49 – 61 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] image radar moirée
[Termes IGN] image TanDEM-X
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle stochastique
[Termes IGN] optimisation (mathématiques)
[Termes IGN] reconstruction 3D du bâtiRésumé : (auteur) Synthetic aperture radar (SAR) systems, such as TanDEM-X, TerraSAR-X and Cosmo-SkyMed, acquire imagery with high spatial resolution (HR), making it possible to observe objects in urban areas with high detail. In this paper, we propose a new top-down framework for three-dimensional (3D) building reconstruction from HR interferometric SAR (InSAR) data. Unlike most methods proposed before, we adopt a generative model and utilize the reconstruction process by maximizing a posteriori estimation (MAP) through Monte Carlo methods. The reason for this strategy refers to the fact that the noisiness of SAR images calls for a thorough prior model to better cope with the inherent amplitude and phase fluctuations.
In the reconstruction process, according to the radar configuration and the building geometry, a 3D building hypothesis is mapped to the SAR image plane and decomposed to feature regions such as layover, corner line, and shadow. Then, the statistical properties of intensity, interferometric phase and coherence of each region are explored respectively, and are included as region terms. Roofs are not directly considered as they are mixed with wall into layover area in most cases. When estimating the similarity between the building hypothesis and the real data, the prior, the region term, together with the edge term related to the contours of layover and corner line, are taken into consideration. In the optimization step, in order to achieve convergent reconstruction outputs and get rid of local extrema, special transition kernels are designed. The proposed framework is evaluated on the TanDEM-X dataset and performs well for buildings reconstruction.Numéro de notice : A2015-851 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.004 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79221
in ISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 49 – 61[article]TerraSAR-X dual-pol time-series for mapping of wetland vegetation / Julie Betbeder in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
[article]
Titre : TerraSAR-X dual-pol time-series for mapping of wetland vegetation Type de document : Article/Communication Auteurs : Julie Betbeder, Auteur ; Sébastien Rapinel, Auteur ; Samuel Corgne, Auteur ; Eric Pottier, Auteur ; Laurence Hubert-Moy, Auteur Année de publication : 2015 Article en page(s) : pp 90 - 98 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] 1:10.000
[Termes IGN] caractérisation
[Termes IGN] carte de la végétation
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données multitemporelles
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] série temporelle
[Termes IGN] zone humideRésumé : (auteur) Mapping vegetation formations at a fine scale is crucial for assessing wetland functions and for better landscape management. Identification and characterization of vegetation formations is generally conducted at a fine scale using ecological ground surveys, which are limited to small areas. While optical remotely sensed imagery is limited to cloud-free periods, SAR time-series are used more extensively for wetland mapping and characterization using the relationship between distribution of vegetation formations and flood duration. The aim of this study was to determine the optimal number and key dates of SAR images to be classified to map wetland vegetation formations at a 1:10,000 scale. A series of eight dual-polarization TerraSAR-X images (HH/VV) was acquired in 2013 during dry and wet seasons in temperate climate conditions. One polarimetric parameter was extracted first, the Shannon entropy, which varies with wetland flooding status and vegetation roughness. Classification runs of all the possible combinations of SAR images using different k (number of images) subsets were performed to determine the best combinations of the Shannon entropy images to identify wetland vegetation formations. The classification runs were performed using Support Vector Machine techniques and were then analyzed using the McNemar test to investigate significant differences in the accuracy of all classification runs based on the different image subsets. The results highlight the relevant periods (i.e. late winter, spring and beginning of summer) for mapping vegetation formations, in accordance with ecological studies. They also indicate that a relationship can be established between vegetation formations and hydrodynamic processes with a short time-series of satellite images (i.e. 5 dates). This study introduces a new approach for herbaceous wetland monitoring using SAR polarimetric imagery. This approach estimates the number and key dates required for wetland management (e.g. restoration) and biodiversity studies using remote sensing data. Numéro de notice : A2015-727 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.05.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78377
in ISPRS Journal of photogrammetry and remote sensing > vol 107 (September 2015) . - pp 90 - 98[article]Web services for dynamic coloring of UAVSAR images / Jun Wang in Pure and applied geophysics, vol 172 n° 8 (August 2015)
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Titre : Web services for dynamic coloring of UAVSAR images Type de document : Article/Communication Auteurs : Jun Wang, Auteur ; Marlon Pierce, Auteur ; Andrea Donnellan, Auteur ; Jay Parker, Auteur Année de publication : 2015 Article en page(s) : pp 2325 - 2332 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] carte thématique
[Termes IGN] cartographie à la volée
[Termes IGN] couleur à l'écran
[Termes IGN] déformation de la croute terrestre
[Termes IGN] drone
[Termes IGN] image radar moirée
[Termes IGN] interface web
[Termes IGN] polarimétrie radar
[Termes IGN] séisme
[Termes IGN] service web géographiqueRésumé : (auteur) QuakeSim has implemented a service-based Geographic Information System to enable users to access large amounts of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data through an online interface. The QuakeSim Interferometric Synthetic Aperture Radar (InSAR) profile tool calculates radar-observed displacement (from an unwrapped interferogram product) along user-specified lines. Pre-rendered thumbnails with InSAR fringe patterns are used to display interferogram and unwrapped phase images on a Google Map in the InSAR profile tool. One challenge with this tool lies in the user visually identifying regions of interest when drawing the profile line. This requires that the user correctly interpret the InSAR imagery, which currently uses fringe patterns. The mapping between pixel color and pixel value is not a one-to-one relationship from the InSAR fringe pattern, and it causes difficulty in understanding general displacement information for QuakeSim users. The goal of this work is to generate color maps that directly reflect the pixel values (displacement) as an addition to the pre-rendered images. Because of an extremely uneven distribution of pixel values on an InSAR image, a histogram-based, nonlinear color template generation algorithm is currently under development. A web service enables on-the-fly coloring of UAVSAR images with dynamically generated color templates. Numéro de notice : A2015-493 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s00024-014-0941-5 Date de publication en ligne : 26/10/2014 En ligne : https://doi.org/10.1007/s00024-014-0941-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77288
in Pure and applied geophysics > vol 172 n° 8 (August 2015) . - pp 2325 - 2332[article]Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data / Laven Naidoo in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
[article]
Titre : Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data Type de document : Article/Communication Auteurs : Laven Naidoo, Auteur ; Renaud Mathieu, Auteur ; Russell Main, Auteur ; Waldo Kleynhans, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 234 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Afrique du sud (état)
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] bande X
[Termes IGN] biomasse
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] image TerraSAR-X
[Termes IGN] savaneRésumé : (auteur) Structural parameters of the woody component in African savannahs provide estimates of carbon stocks that are vital to the understanding of fuelwood reserves, which is the primary source of energy for 90% of households in South Africa (80% in Sub-Saharan Africa) and are at risk of over utilisation. The woody component can be characterised by various quantifiable woody structural parameters, such as tree cover, tree height, above ground biomass (AGB) or canopy volume, each been useful for different purposes. In contrast to the limited spatial coverage of ground-based approaches, remote sensing has the ability to sense the high spatio-temporal variability of e.g. woody canopy height, cover and biomass, as well as species diversity and phenological status – a defining but challenging set of characteristics typical of African savannahs. Active remote sensing systems (e.g. Light Detection and Ranging – LiDAR; Synthetic Aperture Radar – SAR), on the other hand, may be more effective in quantifying the savannah woody component because of their ability to sense within-canopy properties of the vegetation and its insensitivity to atmosphere and clouds and shadows. Additionally, the various components of a particular target’s structure can be sensed differently with SAR depending on the frequency or wavelength of the sensor being utilised. This study sought to test and compare the accuracy of modelling, in a Random Forest machine learning environment, woody above ground biomass (AGB), canopy cover (CC) and total canopy volume (TCV) in South African savannahs using a combination of X-band (TerraSAR-X), C-band (RADARSAT-2) and L-band (ALOS PALSAR) radar datasets. Training and validation data were derived from airborne LiDAR data to evaluate the SAR modelling accuracies. It was concluded that the L-band SAR frequency was more effective in the modelling of the CC (coefficient of determination or R2 of 0.77), TCV (R2 of 0.79) and AGB (R2 of 0.78) metrics in Southern African savannahs than the shorter wavelengths (X- and C-band) both as individual and combined (X + C-band) datasets. The addition of the shortest wavelengths also did not assist in the overall reduction of prediction error across different vegetation conditions (e.g. dense forested conditions, the dense shrubby layer and sparsely vegetated conditions). Although the integration of all three frequencies (X + C + L-band) yielded the best overall results for all three metrics (R2 = 0.83 for CC and AGB and R2 = 0.85 for TCV), the improvements were noticeable but marginal in comparison to the L-band alone. The results, thus, do not warrant the acquisition of all three SAR frequency datasets for tree structure monitoring in this environment. Numéro de notice : A2015-713 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.04.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78353
in ISPRS Journal of photogrammetry and remote sensing > vol 105 (July 2015) . - pp 234 - 250[article]Subsidence monitoring in coal area using time-series InSAR combining persistent scatterers and distributed scatterers / Zhengjia Zhang in International journal of applied Earth observation and geoinformation, vol 39 (July 2015)PermalinkInvariant rules for multipolarization SAR change detection / Vincenzo Carotenuto in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)PermalinkInterferometric phase image estimation via sparse coding in the complex domain / Hao Hongxing in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)PermalinkCAESAR: an approach based on covariance matrix decomposition to improve multibaseline–multitemporal interferometric SAR processing / Gianfranco Fornaro in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)PermalinkPolarimetric SAR speckle filtering and the extended sigma filter / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkTemporal stability of X-band single-pass InSAR heights in a spruce forest: effects of acquisition properties and season / Svein Solberg in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkCalibration of SAR polarimetric images by means of a covariance matching approach / Alberto Villa in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkCapabilities of BIOMASS tomography for investigating tropical forests / Ho Tong Minh Dinh in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkEvaluation and comparison of different radargrammetric approaches for Digital Surface Models generation from COSMO-SkyMed, TerraSAR-X, RADARSAT-2 imagery: Analysis of Beauport (Canada) test site / P. Capaldo in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkFully polarimetric synthetic aperture radar (SAR) processing for crop type identification / Gang Hong in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 2 (February 2015)PermalinkGeometry-information-aided efficient radial velocity estimation for moving target imaging and location based on Radon transform / Xuepan Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkIntegrating SAR and derived products into operational volcano monitoring and decision support systems / Franz J. Meyer in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkMultibaseline polarimetric synthetic aperture radar tomography of forested areas using wavelet-based distribution compressive sensing / Lei Liang in Journal of applied remote sensing, vol 9 (2015)PermalinkPersistent scatterers at building facades – Evaluation of appearance and localization accuracy / Stefan Gernhardt in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkRelating statistical characteristics of cross-polarized phase difference to speckle noise / Huimin Li in Journal of applied remote sensing, vol 9 (2015)PermalinkAnalyse temps-frequence et traitement des signaux RSO à haute résolution spatiale pour la surveillance des grands ouvrages d'art / Andrei Anghel (2015)PermalinkContribution of textural information from TerraSAR-X image for forest mapping / Cécile Cazals (2015)PermalinkFusion of Lidar and SAR data for land-cover mapping in natural environments / Clara Barbanson (2015)PermalinkPerformance assessment of a recent change detection method for homogeneous and heterogeneous images / Jorge Prendes in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)PermalinkSAR-SIFT : a SIFT-like algorithm for SAR images / Flora Dellinger in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkPermalinkSimulating SAR geometric distortions and predicting Persistent Scatterer densities for ERS-1/2 and ENVISAT C-band SAR and InSAR applications: Nationwide feasibility assessment to monitor the landmass of Great Britain with SAR imagery / Francesca Cigna in Remote sensing of environment, vol 152 (September 2014)PermalinkTropical forest change monitoring / David Belton in GEO: Geoconnexion international, vol 13 n° 8 (september 2014)PermalinkSAR change detection based on intensity and texture changes / Maoguo Gong in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)PermalinkAssessment of interferometric DEMs from TerraSAR-X stripmap and spotlight stereopairs: case study in Istanbul / G. Seferick Umut in Photogrammetric record, vol 29 n° 146 (June - August 2014)PermalinkProactive flood monitoring / Sergey Markov in GEO: Geoconnexion international, vol 13 n° 4 (april 2014)PermalinkBenchmarking framework for SAR despeckling / Gerardo Di Martino in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkVegetation height estimation precision with compact PolInSAR and homogeneous random volume over ground model / Aurélien Arnaubec in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkBlind speckle decorrelation for SAR image despeckling / Alessandro Lapini in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkMeasuring deformations using SAR interferometry and GPS observables with geodetic accuracy: Application to Tokyo, Japan / Tamer Elgarbawi in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkModeling and sensing the vertical structure of the atmospheric path delay by microwave radiometry to correct SAR interferograms / Patrizia Basili in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkStudy on the polarimetric characteristics of the Lop Nur arid area using PolSAR data / Zhihong Gao in Journal of applied remote sensing, vol 8 (2014)PermalinkAn innovative support vector machine based method for contextual image classification / Rogério Galante Negri in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkBasal area and biomass estimates of loblolly pine stands using L-band UAVSAR / William L. Marks in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 1 (January 2014)PermalinkMaximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas / Michael Schmitt in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkOrthorectification of full-polarimetric radarsat-2 data using accurate LIDAR DSM / Thierry Toutin in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)PermalinkRadargrammetric registration of airborne multi-aspect SAR data of urban areas / Michael Schmitt in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)PermalinkSAR image categorization with log cumulants of the fractional Fourier transform coefficients / Jagmal Singh in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)PermalinkWavelet-Based Compressed Sensing for SAR Tomography of Forested Areas / Esteban Aguilera in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)PermalinkCoastal wetland mapping combining multi-date SAR and LiDAR / Thomas Richard Allen in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkA comprehensive review of earthquake-induced building damage detection with remote sensing techniques / Laigen Dong in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)PermalinkCorrection and characterization of radio frequency interference signatures in L-band synthetic aperture radar data / Franz J. Meyer in IEEE Transactions on geoscience and remote sensing, vol 51 n° 10 (October 2013)PermalinkNarrow-band interference suppresion for SAR based on independent component analysis / Feng Zhou in IEEE Transactions on geoscience and remote sensing, vol 51 n° 10 (October 2013)PermalinkUsing RFM for simultaneous positioning of multi-sensor spaceborne SAR imagery / Yingdan Wu in Photogrammetric record, vol 28 n° 143 (September - November 2013)PermalinkAn improved PolSAR image speckle reduction algorithm based on structural judgment and hybrid four-component polarimetric decomposition / Zegang Ding in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)Permalink